This is the most comprehensive research covering the IoT market including market by technology, applications, services and specific solutions. This is must have for any vendor looking to either enter into a portion of the IoT market and/or expand offerings into new segments (consumer, enterprise, industrial and/or government) and specific industry verticals. This research includes many reports focused on specific IoT market opportunity areas, consisting of almost three thousand pages of total research. Areas covered include supporting technologies such as 5G in IoT and edge computing as well as core IoT areas such as sensors, devices, and data management. In fact, it includes the most comprehensive research covering core IoT hardware, software, and firmware as well as supporting technologies such as AI and edge computing.

This research includes comprehensive analysis of IoT in connected homes, smart buildings and cities as well as industry-specific IoT solutions such as asset tracking. It also includes IoT managed services with an emphasis on data management in core and edge networks, big data analytics in IoT, and emerging business models for IoT Data as a Service (DaaS). It also includes analysis of the emerging Artificial Intelligence of Things (AIoT), which represents AI support of IoT in which the former as machine learning and decision support and the latter provides connectivity and signaling. This will accelerate the IoT data economy including many opportunities for IoT data syndication in an IoT DaaS model.

This research provides analysis of all major segments (consumer, enterprise, industrial, and government). From an IoT business to business perspective, this research addresses emerging opportunities in enterprise and industrial automation including the use of Industrial IoT (IIoT) solutions involving robotics, teleoperation, and smart machines to automate many business processes beyond the manufacturing environment. Especially within IIoT and enterprise IoT solutions, there is a market need to focus on optimized IoT device management, which is also covered in this research.

The Internet of Things (IoT) is anticipated to have a $7.5 trillion global economic impact in 2020, growing rapidly to approximately $13 trillion by 2025. The economic impact of the IoT market will be in the form of increased global corporate profits, which are estimated to be in the range of a 20% incremental improvement by 2025. These impacts may be viewed as five categories, which are: utilization, employee productivity, supply chain and logistics, customer/citizen experience, and innovation revenue.

Collectively speaking, the aforementioned areas represent the perceived value of the IoT in terms of generated goods and services, value of work opportunity in IoT domain, and value of cost reduction from manufacturing processes, other industrial areas, as well as enterprise automation. The cumulative direct and indirect IoT economic impact will be equivalent to 5% of entire global economy by 2025. Much of this impact will be due to solving problems in a much more efficient manner, such as improved asset tracking, control, and overall management. Significant longer term benefits will rise from completely new products and services as well as new lifecycle support models.

As the size of IoT systems grow to large scale, their scope will also increase in terms of the impact on enterprise systems and consumers everyday lives. 5G will optimize IoT networks by way of radio frequency management that meets the needs of both narrowband IoT applications as well as those that require higher bandwidth, which may be on an on-demand basis. IoT solutions will benefit greatly from the implementation of 5G as cellular providers deploy Low Power WAN (LPWAN) IoT network capabilities. Initial deployments of IoT LPWANs have been non-cellular solutions based on proprietary technologies.

However, Mind Commerce sees emerging standards such as Narrowband IoT (NB-IoT) assuming a dominant role for certain IoT applications. We see many industry verticals willing to pay a premium over non-cellular LPWAN, enhanced flexibility, and improved capabilities associated with IoT on 5G networks. The use of 5G for Industrial IoT (IIoT) networks in particular will be of great importance to enterprise IIoT in certain industry verticals such as agriculture, logistics, and manufacturing. For example, we see IIoT in agriculture benefitting through the use of Unmanned Aerial Vehicle (UAV) operation over 5G networks due to ultra-low latency and high capacity availability.

Deployed in conjunction with 5G, Mobile Edge Computing (MEC),will facilitate an entirely new class of low-power devices for IoT networks and systems. These devices will rely upon MEC equipment for processing. Stated differently, some IoT devices will be very light-weight computationally speaking, relying upon edge computing nodes for most of their computation needs. MEC is also important to 5G for non-IoT applications as support for improved mobile broadband (ultra-fast and high definition video, enhanced web browsing, etc.) and Ultra Reliable Low Latency Communications (URLLC) dependent apps (virtual reality, UAV operation, autonomous vehicles, robotics, etc.).

The “things” involved in IoT varies from devices used to detect, actuate, signal, engage, and more. IoT things also involve everything from gateways, modules, and sensors to hardware and embedded software within products and equipment and other consumer, enterprise, and industrial assets. The IoT ecosystem could easily become highly cumbersome with so many different “things” to consider as part of IoT provisioning, activation, administration and other management functions.

IoT represents a complex system of networks, platforms, interfaces, protocols, devices, and data. IoT devices range from sensors, actuators, gateways, and embedded hardware/software within products and assets. The number and type of IoT devices, as well as the associated use cases for apps and services, grows exponentially within leading industry verticals. One of the critical success factors for IoT operation will be certain Operational Support Systems (OSS) for IoT such as IoT Device Management. As IoT systems and networks grow in complexity and importance, there will be an increasingly urgent need within enterprise, industrial, and government market segments for IoT device management platforms and software.

IoT Device Management encompasses device provisioning, administration, monitoring, and diagnostics important for trouble replication and corrective measures. Important IoT Device Management functions include Enrollment/Provisioning, Configuration/Association, Software Updates, and overall Management and Control. As IoT systems and networks grow in complexity and importance, there will be an increasingly urgent need within enterprise for IoT device management platforms and software. Accordingly, there is a keen need for managed service solutions in support of provisioning, administration, maintenance, and security.

A great majority of industrial companies are currently using IoT solutions for internal business benefits. Future Industrial Internet of Things (IIoT) solutions will focus on strategic differentiation including connected products, greatly improving the supplier-customer relationship. This research evaluates IIoT technologies, companies, applications, services, and solutions. Report forecasts include overall global and regional IIoT outlook as well as IIoT by industry vertical, software, hardware, and services for the period 2019 to 2024.

Industrial Internet of Things (IIoT) solutions are poised to transform many industry verticals including healthcare, retail, automotive, and transport. For many industries, IIoT will significantly improve reliability, production, and customer satisfaction. While, IIoT will initially improve existing processes and augmented current infrastructure, the ultimate goal will be to realize entirely new, and dramatically improved products and services. Successful companies will be those that understand how and where IoT technologies and solutions will drive opportunities for operational improvements, new and enhanced products and services, as well as completely new business models.

IIoT will significantly improve reliability, production, and customer satisfaction. Initially focusing on improving existing processes and augmented current infrastructure, IIoT will rely upon as well as integrate with certain key technologies, devices, software, and applications. IIoT involves a substantial breadth and depth of technologies, many of which require careful integration and orchestration. Leading managed service providers are looking beyond core Machine-to-Machine (M2M) communications towards more advanced services that involve IoT platform and device mediation, data management, and application coordination.

M2M messaging itself is evolving to a more flat hierarchical structure with edge computing networks, which will require managed privacy and security services to ensure data integrity and asset protection. M2M communications for IIoT will become increasingly necessary for enterprise and industrial organizations that wish to fully leverage IoT technologies. Data analytics solutions provide the means to process vast amounts of machine-generated, unstructured data captured by M2M systems. As IIoT progresses, there will an increasingly large amount of unstructured machine data. The growing amount of machine generated industrial data will drive substantial opportunities for AI support of unstructured data analytics solutions.

One clear area of improvement for industrial businesses will be teleoperation and tele-robotics as various industries will leverage the ability to control real machines/equipment by virtual object through master controlling interfaces. Mind Commerce sees teleoperation being transformed by digital twin technologies, which refers to the mapping of the physical world to the digital world in which IoT Platforms and Software are leveraged to create a digital representation of physical object or asset. The digital twin of a physical object can provide data about the asset such as its physical state and disposition.

IoT in industrial settings will create an enormous amount of machine-generated data. The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic. In many cases, the data itself, and actionable information will be the service. However, real-time data is anticipated to become a highly valuable aspect of all solutions as a determinant of user behavior, application effectiveness, and identifier of new and enhanced mobile/wireless and/or IoT related apps and services. These opportunities will require vendors to focus on solutions that involve the use of big data analytics.

However, big data in IoT is different than conventional IoT and thus will requires more robust, agile and scalable platforms, analytical tools and data storage systems than conventional big data infrastructure. Looking beyond data management processes, IoT data itself will become extremely valuable as an agent of change for product development as well as identification of supply gaps and realization of unmet demands. Big data and analytics will increase in importance as IoT evolves to become more commonplace. Data generated through sensors embedded in various things/objects will generate massive amounts of unstructured (big) data on real-time basis that holds the promise for intelligence and insights for dramatically improved decision processes.

Big data in IoT is also dissimilar than non-machine related analytics and thus will require more robust, agile and scalable platforms, analytics tools, and data storage systems than conventional infrastructure. Due to this new architecture approach, the need to handle data differently, and the sheer volume of unstructured data, there will be great opportunities for big Data in IoT. Analytics used in IoT will become an enabler for the entire IoT ecosystem as enterprise begins to take advantage of new business opportunities such as syndicating their own data.

AI enhances the ability for big data analytics and IoT platforms to provide value to each of these market segments. The use of AI for decision making in IoT and data analytics will be crucial for efficient and effective decision making, especially in the area of streaming data and real-time analytics associated with edge computing networks. Real-time data will be a key value proposition for all use cases, segments, and solutions. The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic. In many cases, the data itself, and actionable information will be the service.

AI is also rapidly merging with IoT in general, which will impact current IoT networks, as they are currently largely deterministic in nature, relying upon autonomic systems making decisions based on predetermined rules that take action based upon the occurrence of specific events. Mind Commerce sees the Artificial Intelligence of Things (AIoT) will becoming increasingly important as the AIoT market evolves to allow IoT networks and systems to become more cognitive. In contrast, the emerging AIoT market will enable systems to become increasingly more cognitive, making decisions based on context and experience.

It is important to recognize that intelligence within the IoT technology market is not inherent but rather must be carefully planned. AIoT market elements will be found embedded within software programs, chipsets, and platforms as well as human-facing devices such as appliances, which may rely upon a combination of local and cloud-based intelligence. Just like the human nervous system, IoT networks will have both autonomic and cognitive functional components that provide intelligent control as well as nerve end-points that act like nerve endings for neural transport (detection and triggering of communications) and nerve channels that connect the overall system.

The big difference is that the IoT technology market will benefit from engineering design in terms of AI and cognitive computing placement in both centralized and edge computing locations. It is important to recognize that intelligence within IoT technology market is not inherent but rather must be carefully planned. AIoT market elements will be found embedded within software programs, chipsets, and platforms as well as human-facing devices such as appliances, which may rely upon a combination of local and cloud-based intelligence.

Select Research Findings:

• Embedded AI in support of IIoT smart objects will reach $4.6B globally by 2024
• Hybrid voice and text chatbots market will reach $331.5M USD globally by 2024
• 5G and IoT enabled smart machines represent a $1.2B global opportunity by 2024
• Global asset tracking market for AI in embedded devices will grow at 28.2% through 2024
• Overall market for AI in big data and IoT will be led by Asia Pac followed by North America
• Integrated platforms will lead consumer IoT device management, exceeding $450M by 2024
• Application revenue for edge computing in 5G will reach 40% of infrastructure spending by 2024
• Driven by edge computing, micro-datacenters represent a $1.9B USD opportunity globally by 2024
• IoT technology will need to adapt to support the dynamic between public and private wireless networks
• AI in industrial machines will reach $415M globally by 2024 with collaborative robot growth at 42.5% CAGR
• IoT networks will be multi-vendor with many technologies, necessitating the need for systems integration
• Traditional product companies will shift towards a service-oriented focus with IIoT supporting performance visibility
• IoT systems will become increasingly more cognitive rather than relying solely upon autonomic event-response logic
• IoT solutions will improve lifecycle cost management for facilities and equipment through more intelligence utilization, maintenance, and predictive replacement
• Global Market for Devices in support of Government Security and Monitoring Equipment (CCTVs, Cameras, etc.) and Structural Health Monitoring Devices will reach $4.6 Billion USD by 2024